Steven Farrell

Publication Activity (10 Years)

Years Active: 2018-2023
Publications (10 Years): 15

Top Topics

Benchmark Suite

High Energy Physics

Challenging Sequences

Top Venues

J. Chem. Inf. Model.

Publications

Ryan Liu, Paolo Calafiura, Steven Farrell, Xiangyang Ju, Daniel Thomas Murnane, Tuan Minh Pham
Hierarchical Graph Neural Networks for Particle Track Reconstruction. CoRR (2023)
Chunhui Li, Benjamin Gilbert, Steven Farrell, Piotr Zarzycki
Rapid Prediction of a Liquid Structure from a Single Molecular Configuration Using Deep Learning. J. Chem. Inf. Model. 63 (12) (2023)
Sabrina Amrouche, Laurent Basara, Paolo Calafiura, Dmitry Emeliyanov, Victor Estrade, Steven Farrell, Cécile Germain, Vladimir Vava Gligorov, Tobias Golling, Sergey Gorbunov, Heather M. Gray, Isabelle Guyon, Mikhail Hushchyn, Vincenzo Innocente, Moritz Kiehn, Marcel Kunze, Edward Moyse, David Rousseau, Andreas Salzburger, Andrey Ustyuzhanin, Jean-Roch Vlimant
The Tracking Machine Learning Challenge: Throughput Phase. Comput. Softw. Big Sci. 7 (1) (2023)
Xiangyang Ju, Yunsong Wang, Daniel Murnane, Nicholas Choma, Steven Farrell, Paolo Calafiura
Benchmarking GPU and TPU Performance with Graph Neural Networks. CoRR (2022)
Xiangyang Ju, Daniel Murnane, Paolo Calafiura, Nicholas Choma, Sean Conlon, Steven Farrell, Yaoyuan Xu, Maria Spiropulu, Jean-Roch Vlimant, Adam Aurisano, Jeremy Hewes, Giuseppe Cerati, Lindsey Gray, Thomas Klijnsma, Jim Kowalkowski, Markus Atkinson, Mark Neubauer, Gage DeZoort, Savannah Thais, Aditi Chauhan, Alex Schuy, Shih-Chieh Hsu, Alexandra Ballow, Alina Lazar
Physics and Computing Performance of the Exa.TrkX TrackML Pipeline. CoRR (2021)
Charlene Yang, Yunsong Wang, Thorsten Kurth, Steven Farrell, Samuel Williams
Hierarchical Roofline Performance Analysis for Deep Learning Applications. SAI (2) (2021)
Steven Farrell, Murali Emani, Jacob Balma, Lukas Drescher, Aleksandr Drozd, Andreas Fink, Geoffrey C. Fox, David Kanter, Thorsten Kurth, Peter Mattson, Dawei Mu, Amit Ruhela, Kento Sato, Koichi Shirahata, Tsuguchika Tabaru, Aristeidis Tsaris, Jan Balewski, Ben Cumming, Takumi Danjo, Jens Domke, Takaaki Fukai, Naoto Fukumoto, Tatsuya Fukushi, Balazs Gerofi, Takumi Honda, Toshiyuki Imamura, Akihiko Kasagi, Kentaro Kawakami, Shuhei Kudo, Akiyoshi Kuroda, Maxime Martinasso, Satoshi Matsuoka, Henrique Mendonça, Kazuki Minami, Prabhat Ram, Takashi Sawada, Mallikarjun Shankar, Tom St. John, Akihiro Tabuchi, Venkatram Vishwanath, Mohamed Wahib, Masafumi Yamazaki, Junqi Yin
MLPerf™ HPC: A Holistic Benchmark Suite for Scientific Machine Learning on HPC Systems. MLHPC@SC (2021)
Khaled Z. Ibrahim, Tan Nguyen, Hai Ah Nam, Wahid Bhimji, Steven Farrell, Leonid Oliker, Michael Rowan, Nicholas J. Wright, Samuel Williams
Architectural Requirements for Deep Learning Workloads in HPC Environments. PMBS (2021)
Sabrina Amrouche, Laurent Basara, Paolo Calafiura, Dmitry Emeliyanov, Victor Estrade, Steven Farrell, Cécile Germain, Vladimir Vava Gligorov, Tobias Golling, Sergey Gorbunov, Heather Gray, Isabelle Guyon, Mikhail Hushchyn, Vincenzo Innocente, Moritz Kiehn, Marcel Kunze, Edward Moyse, David Rousseau, Andreas Salzburger, Andrey Ustyuzhanin, Jean-Roch Vlimant
The Tracking Machine Learning challenge : Throughput phase. CoRR (2021)
Steven Farrell, Murali Emani, Jacob Balma, Lukas Drescher, Aleksandr Drozd, Andreas Fink, Geoffrey C. Fox, David Kanter, Thorsten Kurth, Peter Mattson, Dawei Mu, Amit Ruhela, Kento Sato, Koichi Shirahata, Tsuguchika Tabaru, Aristeidis Tsaris, Jan Balewski, Ben Cumming, Takumi Danjo, Jens Domke, Takaaki Fukai, Naoto Fukumoto, Tatsuya Fukushi, Balazs Gerofi, Takumi Honda, Toshiyuki Imamura, Akihiko Kasagi, Kentaro Kawakami, Shuhei Kudo, Akiyoshi Kuroda, Maxime Martinasso, Satoshi Matsuoka, Henrique Mendonça, Kazuki Minami, Prabhat Ram, Takashi Sawada, Mallikarjun Shankar, Tom St. John, Akihiro Tabuchi, Venkatram Vishwanath, Mohamed Wahib, Masafumi Yamazaki, Junqi Yin
MLPerf HPC: A Holistic Benchmark Suite for Scientific Machine Learning on HPC Systems. CoRR (2021)
Yunsong Wang, Charlene Yang, Steven Farrell, Yan Zhang, Thorsten Kurth, Samuel Williams
Time-Based Roofline for Deep Learning Performance Analysis. DLS@SC (2020)
Nicholas Choma, Daniel Murnane, Xiangyang Ju, Paolo Calafiura, Sean Conlon, Steven Farrell, Prabhat, Giuseppe Cerati, Lindsey Gray, Thomas Klijnsma, Jim Kowalkowski, Panagiotis Spentzouris, Jean-Roch Vlimant, Maria Spiropulu, Adam Aurisano, Jeremy Hewes, Aristeidis Tsaris, Kazuhiro Terao, Tracy L. Usher
Track Seeding and Labelling with Embedded-space Graph Neural Networks. CoRR (2020)
Yunsong Wang, Charlene Yang, Steven Farrell, Yan Zhang, Thorsten Kurth, Samuel Williams
Time-Based Roofline for Deep Learning Performance Analysis. CoRR (2020)
Yunsong Wang, Charlene Yang, Steven Farrell, Thorsten Kurth, Samuel Williams
Hierarchical Roofline Performance Analysis for Deep Learning Applications. CoRR (2020)
Paolo Calafiura, Steven Farrell, Heather Gray, Jean-Roch Vlimant, Vincenzo Innocente, Andreas Salzburger, Sabrina Amrouche, Tobias Golling, Moritz Kiehn, Victor Estrade, Cécile Germain, Isabelle Guyon, Ed Moyse, David Rousseau, Yetkin Yilmaz, Vladimir Vava Gligorov, Mikhail Hushchyn, Andrey Ustyuzhanin
TrackML: A High Energy Physics Particle Tracking Challenge. eScience (2018)